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Structured vs. Unstructured Data​: Understanding the Differences and Why They Matter

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Data Driven World
March 30, 2023

In today's digital age, data is becoming increasingly important for businesses to make informed decisions. However, not all data is created equal, and it is essential to understand the differences between structured and unstructured data.

Structured data refers to data that is organized in a specific format that is easy to store, process, and analyze. This type of data is typically numerical or categorical and is stored in databases and spreadsheets. Structured data is characterized by having a defined data model, such as tables with rows and columns. It is easily searchable and sortable, making it simpler to extract insights and make informed decisions.

On the other hand, unstructured data refers to data that lacks a clear data model and is not organized in a predefined manner. This type of data includes text documents, images, videos, social media posts, and other types of media. Unstructured data is not easily searchable or sortable and requires specialized tools and techniques to analyze.

As per projections from IDC, 80% of global data will be unstructured by 2025. For some huge organizations, it has already reached that critical mass. This means that businesses need to be prepared to deal with unstructured data and have the tools and techniques necessary to analyze it effectively.

In conclusion, while structured data is easy to work with and provides quick insights, unstructured data can also provide valuable insights if analyzed properly. Therefore, it is essential for businesses to understand the differences between these two types of data and have the necessary tools and techniques to work with both.

Structured Vs Unstructured Data

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